📝 Overview This project implements a Convolutional Neural Network (CNN) for binary image classification. The model features automated data preprocessing, GPU optimization, and comprehensive ...

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With fake images, we can customize the exact properties of the objects in the image. That way, we can see if the algorithms we’re training can uncover those properties correctly.

Deep underwater color images have problems such as low brightness, poor contrast, and loss of local details. In order to effectively enhance low-quality underwater images, this paper proposes an ...

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This brief presents an efficient binary neural network inference processor, that is, resilient to soft errors caused by potential circuit faults. The proposed p ...